Age‐related changes in fiber tracts in healthy adult brains: A generalized q‐sampling and connectometry study

Liu, Xiaojing; Gao, Xiaodong; Zhang, Li; Yuan, Zheng; Zhang, Chen; Lu, Weizhao; Cui, Dong; Zheng, Fenglian; Qiu, Jianfeng; Xie, Jun

doi:10.1002/jmri.25949

Cited by 10 publications

(9 citation statements)

References 40 publications

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“…However, we found that the length of fibers in the ACR, SLF_L, PCR_R, PTR_L, SCC, and PLIC regions increases with age. These results are generally consistent with some other observations obtained in our lab, which show that the fiber lengths in SCC, PCR, and PTR regions increase with age (Liu et al, 2018 ).…”

Section: Discussionsupporting

confidence: 93%

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Analysis of Age-Related White Matter Microstructures Based on Diffusion Tensor Imaging

Ouyang

Cui

Yuan

et al. 2021

Front. Aging Neurosci.

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Population aging has become a serious social problem. Accordingly, many researches are focusing on changes in brains of the elderly. In this study, we used multiple parameters to analyze age-related changes in white matter fibers. A sample cohort of 58 individuals was divided into young and middle-age groups and tract-based spatial statistics (TBSS) were used to analyze the differences in fractional anisotropy (FA), mean diffusion (MD), axial diffusion (AD), and radial diffusion (RD) between the two groups. Deterministic fiber tracking was used to investigate the correlation between fiber number and fiber length with age. The TBSS analysis revealed significant differences in FA, MD, AD, and RD in multiple white matter fibers between the two groups. In the middle-age group FA and AD were lower than in young people, whereas the MD and RD values were higher. Deterministic fiber tracking showed that the fiber length of some fibers correlated positively with age. These fibers were observed in the splenium of corpus callosum (SCC), the posterior limb of internal capsule (PLIC), the right posterior corona radiata (PCR_R), the anterior corona radiata (ACR), the left posterior thalamic radiation (include optic radiation; PTR_L), and the left superior longitudinal fasciculus (SLF_L), among others. The results showed that the SCC, PLIC, PCR_R, ACR, PTR_L, and SLF_L significantly differed between young and middle-age people. Therefore, we believe that these fibers could be used as image markers of age-related white matter changes.

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Section: Discussionsupporting

confidence: 93%

“…ROI regions from the TBSS analyses were imported into the DSI-studio for fiber tracking. As per our previous reports (Liu et al, 2018 ), the fiber tracking parameters were set as follows: FA was 0.15, the step size was 0.47, and the angular threshold was less than 60°. Additionally, tract lengths were restricted to 30–300 mm in length.…”

Section: Methodsmentioning

confidence: 99%

Analysis of Age-Related White Matter Microstructures Based on Diffusion Tensor Imaging

Ouyang

Cui

Yuan

et al. 2021

Front. Aging Neurosci.

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“…One of the most enduring findings from diffusion tensor imaging (DTI) studies across the lifespan is the regionally selective distribution of low fractional anisotropy (FA) in frontal white matter with increasing age (Bennett and Madden, 2014;Bhagat and Beaulieu, 2004;Cox et al, 2016;Head et al, 2004;Madden et al, 2012;Pfefferbaum et al, 2005;Rojkova et al, 2016;Salat et al, 2005;Sexton et al, 2014;Vik et al, 2015;Zhang et al, 2010), a finding thathas been corroborated in non-human primates (Kubicki et al, 2018;Makris et al, 2007). An anteriorto-posterior gradient of fiber integrity, in which anterior fiber bundles are more susceptible to age-related degeneration than posterior fibers, has also been demonstrated in the corpus callosum using a variety of analytic approaches, including region-of-interest (ROI) analysis (Bender et al, 2016b;Madden et al, 2012;O'Sullivan et al, 2001;Pfefferbaum et al, 2005;Pfefferbaum and Sullivan, 2003;Salat et al, 2005;Sexton et al, 2014;Xie et al, 2016), voxel-based approaches (Hsu et al, 2008;Salat et al, 2005;Sexton et al, 2014;Zhang et al, 2010), and tract-based analyses (Bennett et al, 2010;Burzynska et al, 2010;Davis et al, 2009;Fjell et al, 2017;Lebel et al, 2012;Liu et al, 2018;Sala et al, 2012;Sullivan et al, 2001Sullivan et al, , 2010.…”

Section: Introductionmentioning

confidence: 89%

“…Noninvasive approaches to infer axon size and density in the living human brain would be invaluable for understanding the microstructural substrate of age-related degeneration of cerebral white matter. The trends in callosal fiber composition identified on histology are supported by multiple neuroimaging studies that have used diffusion magnetic resonance imaging (MRI) to infer white matter microstructural properties in the aging human brain (Abe et al, 2002;Bender et al, 2016b;Bennett and Madden, 2014;Berman et al, 2018;Bhagat and Beaulieu, 2004;Billiet et al, 2015;Branzoli et al, 2016;Chad et al, 2018;Cox et al, 2016;de Lange et al, 2016;Fjell et al, 2016Fjell et al, , 2017Head et al, 2004;Hsu et al, 2008;Lebel et al, 2010;Liu et al, 2018;Madden et al, 2004;Martensson et al, 2018;Moseley, 2002;Nusbaum et al, 2001;Ota et al, 2006;Pfefferbaum et al, 2000Pfefferbaum et al, , 2005Salat et al, 2005;Serbruyns et al, 2015;Sexton et al, 2014;Storsve et al, 2016;Stricker et al, 2015;Sullivan et al, 2001Wang et al, 2018;Xie et al, 2016;Yeatman et al, 2014). One of the most enduring findings from diffusion tensor imaging (DTI) studies across the lifespan is the regionally selective distribution of low fractional anisotropy (FA) in frontal white matter with increasing age (Bennett and Madden, 2014;Bhagat and Beaulieu, 2004;Cox et al, 2016;…”

Section: Introductionmentioning

confidence: 92%

Age-related alterations in axonal microstructure in the corpus callosum measured by high-gradient diffusion MRI

et al. 2019

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Cerebral white matter exhibits age-related degenerative changes during the course of normal aging, including decreases in axon density and alterations in axonal structure. Noninvasive approaches to measure these microstructural alterations throughout the lifespan would be invaluable for understanding the substrate and regional variability of age-related white matter degeneration. Recent advances in diffusion magnetic resonance imaging (MRI) have leveraged high gradient strengths to increase sensitivity toward axonal size and density in the living human brain. Here, we examined the relationship between age and indices of axon diameter and packing density using high-gradient strength diffusion MRI in 36 healthy adults (aged 22-72) in welldefined central white matter tracts in the brain. A recently validated method for inferring the effective axonal compartment size and packing density from diffusion MRI measurements acquired with 300 mT/m maximum gradient strength was applied to the in vivo human brain to obtain indices of axon diameter and density in the corpus callosum, its sub-regions, and adjacent anterior and posterior fibers in the forceps minor and forceps major. The relationships between the axonal metrics, corpus callosum area and regional gray matter volume were also explored. Results revealed a significant increase in axon diameter index with advancing age in the whole corpus callosum. Similar analyses in sub-regions of the corpus callosum showed that age-related alterations in axon diameter index and axon density were most pronounced in the genu of the corpus callosum and relatively absent in the splenium, in keeping with findings from previous histological studies. The significance of these correlations was mirrored in the forceps minor and forceps major, consistent with previously reported decreases in FA in the forceps minor but not in the forceps major with age. Alterations in the axonal imaging metrics paralleled decreases in

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“…While diffusivity and density results sometimes converge, SDF may be more robust to crossing fibers and partial volume effects. 27 Additionally, density measures have shown increased sensitivity in both healthy aging 28 and clinical populations. 29 Investigations of white matter density in bipolar disorder are scarce, but several studies examined white matter diffusivity (FA and RD) in this population.…”

Section: Introductionmentioning

confidence: 99%

Reduced white matter microstructure in bipolar disorder with and without psychosis

et al. 2021

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Objectives: Affective and psychotic features overlap considerably in bipolar I disorder, complicating efforts to determine its etiology and develop targeted treatments.In order to clarify whether mechanisms are similar or divergent for bipolar disorder with psychosis (BDP) and bipolar disorder with no psychosis (BDNP), neurobiological profiles for both the groups must first be established. This study examines white matter structure in the BDP and BDNP groups, in an effort to identify portions of white matter that may differ between the bipolar and healthy groups or between the bipolar subgroups themselves. Methods: Diffusion-weighted imaging data were acquired from participants with BDP (n = 45), BDNP (n = 40), and healthy comparisons (HC) (n = 66). Fractional anisotropy (FA), radial diffusivity (RD), and spin distribution function (SDF) values indexing white matter diffusivity or spin density were calculated and compared between the groups. Results:In comparisons between both the bipolar groups and HC, FA (FDR < 0.00001) and RD (FDR = 0.0037) differed minimally, in localized portions of the left cingulum and corpus callosum, while reductions in SDF (FDR = 0.0002) were more widespread.The bipolar subgroups did not differ from each other on FA, RD, or SDF metrics.Conclusions: Together, these results demonstrate a novel profile of white matter differences in bipolar disorder and suggest that this white matter pathology is associated with the affective disturbance common to those with bipolar disorder rather than the psychotic features unique to some. The white matter alterations identified in this study may provide substrates for future studies examining specific mechanisms that target affective domains of illness.

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Age‐related changes in fiber tracts in healthy adult brains: A generalized q‐sampling and connectometry study

Abstract: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2018;48:369-381.

Cited by 10 publications

References 40 publications

Analysis of Age-Related White Matter Microstructures Based on Diffusion Tensor Imaging

Analysis of Age-Related White Matter Microstructures Based on Diffusion Tensor Imaging

Age-related alterations in axonal microstructure in the corpus callosum measured by high-gradient diffusion MRI

Reduced white matter microstructure in bipolar disorder with and without psychosis

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